Abstract

This paper proposes that two significant and emerging problems facing our connected, data-driven
society may be more effectively solved by being framed as sensemaking challenges. The first is in
empowering individuals to take control of their privacy, in device-rich information environments
where personal information is fed transparently to complex networks of information brokers. Although
sensemaking is often framed as an analytical activity undertaken by experts, due to the fact that
non-specialist end-users are now being forced to make expert-like decisions in complex information
environments, we argue that it is both appropriate and important to consider sensemaking challenges
in this context. The second is in supporting human-in-the-loop algorithmic decision-making, in which
important decisions bringing direct consequences for individuals, or indirect consequences for groups,
are made with the support of data-driven algorithmic systems. In both privacy and algorithmic decision-making, framing the problems as sensemaking challenges acknowledges complex and illdefined
problem structures, and affords the opportunity to view these activities as both building up
relevant expertise schemas over time, and being driven potentially by recognition-primed decision
making.

Type:

Proceedings paper

Title:

The Need for Sensemaking in Networked Privacy and Algorithmic Responsibility

Event:

ACM Conference on Human Factors in Computing Systems (CHI'18)

Location:

Montréal, Canada

Dates:

21 April 2018 - 27 April 2018

Open access status:

An open access version is available from UCL Discovery

Language:

English

Additional information:

This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.